Reminder_Bot

Reminder_Bot is a Telegram bot project built using the Python libraries aiogram and SQLAlchemy. The bot's purpose is to help users set reminders and receive regular reminder messages on their mobile devices.

To use the bot, a user can search for it in the Telegram app @Reminder013_Bot or click on the provided invite link to add it to their contacts. Once added, the user can create one-time or multiple reminders by interacting with the bot. The user can specify the date, time, and message content for the reminder using the bot's interface.

The bot then stores the reminder details in a database using the SQLAlchemy library. The bot periodically checks the database for upcoming reminders, and when it's time for a reminder to be sent, the bot uses the aiogram library to send a reminder message to the user. The reminder message will include the message content that the user provided when creating the reminder.

The bot is designed to be reliable and easy to use, with a simple and intuitive interface that makes setting and managing reminders a breeze. It's a great tool for busy individuals who want to stay on top of their schedule and make sure they don't forget important tasks or appointments.

About the structure

Structure:

tgbot/
├── bot.py
├── tgbot/
│   ├── __init__.py
│   ├── config.py
│   ├── filters/
│   ├── handlers/
│   └── middlewares/

• The tgbot package is the root package for the bot, and it contains sub-packages for filters, handlers, and middlewares.

• The filters package contains classes that define custom filters for the bot's message handlers.

• The handlers package contains classes that define the bot's message handlers, which specify the actions to take in response to incoming messages.

• The middlewares package contains classes that define custom middlewares for the bot's dispatcher, which can be used to perform additional processing on incoming messages.

Detailed description

bot.py

The bot.py script is the entry point for the template Telegram bot. It performs the following steps to start and run the bot:

1. Set up logging: The logging module is imported and configured to log messages to the console.
2. Load the configuration: The load_config() function from the tgbot.config module is called to read the configuration from the environment.
3. Set up the storage: Depending on the use_redis flag in the configuration, either a MemoryStorage or a RedisStorage2 instance is created to store the bot's state.
4. Create the bot and the dispatcher: A Bot instance is created using the bot token from the configuration, and a Dispatcher instance is created using the Bot instance and the storage.
5. Register middlewares, filters, and handlers: The register_all_middlewares(), register_all_filters(), and register_all_handlers() functions are called to register all the middlewares, filters, and handlers that are used by the bot.
6. Start the polling loop: The start_polling() method of the Dispatcher instance is called to start the main event loop for the bot. This method listens for incoming messages and routes them to the appropriate handler.

tgbot/config.py

The config.py script defines a data structure for storing configuration options for the bot, such as the Telegram bot token, database credentials, and other parameters.

The config.py script also includes a load_config function for loading the configuration from a file using the environs library.

The config.py file defines a Config class, which is used to store configuration settings for the bot.

The Config class has three nested classes, TgBot, DbConfig, and Miscellaneous, which are used to store configuration settings for the Telegram bot, the database, and miscellaneous settings, respectively.

The load_config function is used to load the configuration settings from an environment file and create a Config object.

tgbot/filters/admin.py

The admin.py file defines an AdminFilter class, which is used to filter messages so that only messages from authorized users (i.e., users who are listed in the ADMINS configuration setting) are processed by the bot.

The AdminFilter class is a subclass of BoundFilter from the aiogram library, and it defines a key property that specifies the name of the filter. The AdminFilter class also defines an __init__ method that takes a is_admin parameter, which specifies whether the user who sent the message is an authorized user.

The AdminFilter class also defines a check method that checks whether the user who sent the message is an admin user, and if so, it returns True, indicating that the message should be processed by the bot. Otherwise, it returns False, indicating that the message should be ignored by the bot. The check method is called by the bot's dispatcher when a message is received.

tgbot/handlers/admin.py

The admin.py file defines a register_admin function, which is used to register event handlers for messages that are sent by authorized users (i.e., users who are listed in the ADMINS configuration setting).

The register_admin function takes a Dispatcher object as its parameter, and it uses this object to register event handlers that respond to different types of messages.

For example, it might register an event handler that responds to commands that are sent by authorized users, such as the /echo command, which causes the bot to repeat the text of the message back to the user.

tgbot/middlewares/environment.py

environment.py is a file that contains the EnvironmentMiddleware class, which is a middleware used in the Telegram bot.

A middleware is a piece of code that sits between the incoming request and the handler function. In this case, the EnvironmentMiddleware class allows the bot to access the configuration data that was loaded by the load_config function in the config.py file. This configuration data can then be accessed by other parts of the bot, such as the handlers, to customize its behavior.

tgbot/keyboards/(inline|reply).py

The inline.py and reply.py files define classes that are used to create inline and reply keyboards, respectively.

The InlineKeyboard class is a subclass of InlineKeyboardMarkup from the aiogram library, and it defines a __init__ method that takes a inline_keyboard parameter, which specifies the buttons that should be included in the keyboard.

The ReplyKeyboard class is a subclass of ReplyKeyboardMarkup from the aiogram library, and it defines a __init__ method that takes a keyboard parameter, which specifies the buttons that should be included in the keyboard.

tgbot/misc

In general, a package called "misc" might be used to store miscellaneous code that doesn't fit into any of the other packages or modules in a project. This could include utility functions, helper classes, or other types of code that are used by multiple parts of the project.

In this case, the misc package contains a states.py file, which defines a StateGroup class that is used to define the states that are used by the bot.

tgbot/models

The models package can contain users.py file, which defines a User class that is used to represent a user in the database. This can be used with combination of some ORM (Object Relational Mapper) to store and retrieve data from the database.

tgbot/services

This package can also be named infrastructure. It contains the code that is used to interact with external services.

A package called "services" could contain code that defines services that are used by an application. In software development, a service is a self-contained piece of functionality that performs a specific task or provides a specific capability. A service is typically defined as a class or a set of functions that implement the desired functionality.

Examples of services that might be included in a services package could include a database access service, a caching service, a messaging service, or any other type of functionality that is used by the application. The exact contents of a services package would depend on the specific needs of the application and the services that it requires.

The services package can contain a database.py file, which defines a Database class that is used to connect to the database and perform database operations.

docker-compose.yml

The docker-compose.yml file defines the services that are used by the application, as well as the networks and volumes that are needed by the application. The file begins by specifying the version of the Docker Compose file format that is being used.

The services section of the file defines the containers that should be run as part of the application. In this example, there is only one service, called bot, which is based on the tg_bot-image Docker image. The container_name specifies the name that should be used for the container, and the build section specifies the location of the Dockerfile that should be used to build the image.

The working_dir specifies the working directory that should be used by the container, and the volumes section specifies the files and directories that should be mounted into the container. In this case, the entire project directory is mounted into the container, which allows the application to access the files on the host machine.

The command specifies the command that should be run when the container is started, and the restart setting specifies that the container should be automatically restarted if it exits.

The env_file setting specifies the location of the .env file, which contains the configuration settings for the application.

The networks section defines the networks that the container should be connected to. In this example, there is only one network, called tg_bot, which is based on the bridge driver. This network allows the containers in the application to communicate with each other.

Dockerfile

The Dockerfile defines the instructions for building the Docker image that is used by the bot service. The file begins by specifying the base image that should be used for the image, which in this case is python:3.11. The ENV instruction sets the value of the BOT_NAME environment variable, which is used by the WORKDIR instruction to specify the working directory for the container.

The COPY instructions are used to copy the requirements.txt file and the entire project directory into the image. The RUN instruction is used to install the Python dependencies from the requirements.txt file. This allows the application to run in the container with all the necessary dependencies.